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Study on Automatic Classification of Arrhythmias

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Book cover Feature Engineering and Computational Intelligence in ECG Monitoring

Abstract

Electrocardiogram (ECG) signals reveal the electrical activity of the heart and can be used to diagnose heart abnormalities. In the past few decades, ECG signals have been utilized for automatic arrhythmia detection owing to the noninvasive nature and convenience of electrocardiography. However, it is difficult to extract and select reliable features or design robust and generic classifiers because of the complexity and diversity of ECG signals. Consequently, improving the classification rate of arrhythmias still remains a considerable challenge. To resolve this pressing issue, we have proposed a model composed of preprocessing, feature extraction, and classification, where the correct implementation of each part is crucial for final arrhythmia identification. In this chapter, the literature on existing algorithms is comprehensively reviewed according to the aforementioned primary aspects.

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Authors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China

    Runnan He, Yang Liu & Henggui Zhang

  2. Biological Physics Group, Department of Physics and Astronomy, University of Manchester, Manchester, UK

    Henggui Zhang

  3. Peng Cheng Laboratory, Shenzhen, China

    Henggui Zhang

  4. Pilot National Laboratory of Marine Science and Technology, Qingdao, China

    Henggui Zhang

  5. International Laboratory for Smart Systems and Key Laboratory of Intelligent of Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, China

    Henggui Zhang

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  1. Runnan He
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  2. Yang Liu
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  3. Henggui Zhang
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Correspondence to Runnan He .

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Editors and Affiliations

  1. The State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing, China

    Chengyu Liu

  2. School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China

    Jianqing Li

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He, R., Liu, Y., Zhang, H. (2020). Study on Automatic Classification of Arrhythmias. In: Liu, C., Li, J. (eds) Feature Engineering and Computational Intelligence in ECG Monitoring. Springer, Singapore. https://doi.org/10.1007/978-981-15-3824-7_7

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